Adaptive evolution of non coding DNA and gene expression divergence in Drosophila

描述（由申请人提供）：越来越多的证据支持这样一种观点，即调控进化——基因表达的地点和时间的进化——是高等生物模块化组织、功能多样化和新性状起源背后的主要遗传机制。真核生物基因组中调节基因表达的大部分元件位于非编码DNA（即不编码蛋白质的DNA）中。最近的研究表明，黑腹果蝇基因组的大部分非编码部分是进化受限的，这意味着这些区域对生物体的适应度很重要，可能是大量适应性进化的目标。我们建议使用新的计算和实验方法相结合的方法来：1)鉴定可能是周期性适应进化目标的顺式调控非翻译转录区（utr）； 2)实验测试假设的功能取代对物种间基因表达差异水平的影响。我们将首先收集25个天然菌株的种群基因组变异性数据，包括所有5<和3< utr的全长转录本（~2.2Mb）和一个由紧密连接的短内含子和编码序列（~5.8Mb）组成的对照参考面板。我们将使用并进一步开发计算方法，利用这种群体遗传数据来识别物种之间积累了适应性序列差异的utr。具体而言，我们将探索利用等位基因频谱并将这些新数据与新兴的黑腹龙葵种群基因组数据相结合，在多大程度上可以提高种群基因测试的保真度，以进行选择。然后，我们将使用D. melanogaster作为实验模型，对基于计算方法的预测进行功能验证。具体来说，我们将使用转基因共放置方法来确定3<UTR差异对基因表达差异的影响，并测试关于个体功能取代如何相互作用并促进基因表达变化的其他假设。反过来，这些实验将用于改进我们的计算预测方法。这项研究将确定新的顺式调控元件，开发新的方法来绘制这些元件，并为基因调控变化如何导致新物种的进化和动物形式的多样性提供重要的见解。我们开发的计算方法和生物直觉将广泛适用于其他模型系统，包括人类。

DESCRIPTION (provided by applicant): A growing body of evidence supports the view that regulatory evolution - the evolution of where and when a gene is expressed - is the primary genetic mechanism behind the modular organization, functional diversification, and origin of novel traits in higher organisms. Most elements regulating gene expression in eukaryotic genomes reside in noncoding DNA (i.e. DNA that does not encode protein). Recent studies suggest that much of the noncoding portion of the Drosophila melanogaster genome is evolutionarily constrained, implying that these regions are important for an organism<s fitness and may be the target of substantial adaptive evolution. We propose to use a combination of novel computational and experimental approaches to 1) identify cis-regulatory untranslated transcribed regions (UTRs) that may have been targets of recurrent adaptive evolution and 2) experimentally test the effects of putatively functional substitutions on levels of gene expression divergence between species. We will begin by collecting population genomic variability data from 25 naturally occurring strains of D. simulans for all 5< and 3<UTRs with full length transcripts (~2.2Mb) and a control reference panel of closely-linked short introns and coding sequence (~5.8Mb). We will use and further develop computational methods to identify UTRs that have accumulated adaptive sequence divergence between species using population genetic data of this kind. Specifically, we will explore to what extent using the allelic frequency spectrum and integrating this new data with emerging population genomic data for D. melanogaster can improve the fidelity of population genetic tests for selection. We will then use D. melanogaster as an experimental model to functionally verify predictions based on computational methods. Specifically, we will use a transgene co-placement method to determine the effects of 3<UTR divergence on gene expression divergence and test alternative hypotheses about how individual functional substitutions interact and contribute to changes in gene expression. These experiments will, in turn, be used to refine our computational prediction methods. This research will identify new cis- regulatory elements, develop novel methodologies for mapping such elements and provide important insights into how gene regulatory changes have led to the evolution of new species and diversity in animal forms. The computational methods and biological intuitions we develop will be widely applicable to other model systems, including humans. PUBLIC HEALTH RELEVANCE: Changes in genetic regulation contribute to adaptations in natural populations and influence susceptibility to human diseases (Gilad et al. 2008; Gobbi et al. 2006). Despite their potential phenotypic importance, the selective pressures acting on regulatory processes and gene expression levels in particular are largely unknown. Our research combines computational and experimental approaches to study how natural selection acts on genetic variation underlying both beneficial and detrimental functional differences in gene expression. This work will significantly improve our understanding of biology of human diseases caused by the misexpression of genes.